IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v225y2018icp797-813.html
   My bibliography  Save this article

A maximum entropy approach to the estimation of spatially and sectorally disaggregated electricity load curves

Author

Listed:
  • Többen, Johannes
  • Schröder, Thomas

Abstract

Usually, disaggregated electricity load curves are estimated by using Top-Down or Bottom-Up approaches. The former requires estimating weightings for downscaling aggregated information, while the latter requires extrapolating micro-level information. In both cases, estimation would ideally be based on as much regional and sector specific information as possible, in order to obtain a realistic representation of the magnitude and temporal pattern of a regional sector’s electricity consumption. Typically, such attempts are significantly hampered by issues of limited and possibly inconsistent data, differing levels of detail, and mismatching data classifications.

Suggested Citation

  • Többen, Johannes & Schröder, Thomas, 2018. "A maximum entropy approach to the estimation of spatially and sectorally disaggregated electricity load curves," Applied Energy, Elsevier, vol. 225(C), pages 797-813.
    • Handle: RePEc:eee:appene:v:225:y:2018:i:c:p:797-813
    DOI: 10.1016/j.apenergy.2018.04.126
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261918306913
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2018.04.126?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Arne Stolbjerg Drud, 1994. "CONOPT—A Large-Scale GRG Code," INFORMS Journal on Computing, INFORMS, vol. 6(2), pages 207-216, May.
    2. Viegas, Joaquim L. & Vieira, Susana M. & Melício, R. & Mendes, V.M.F. & Sousa, João M.C., 2016. "Classification of new electricity customers based on surveys and smart metering data," Energy, Elsevier, vol. 107(C), pages 804-817.
    3. Xiang, Yue & Liu, Junyong & Li, Ran & Li, Furong & Gu, Chenghong & Tang, Shuoya, 2016. "Economic planning of electric vehicle charging stations considering traffic constraints and load profile templates," Applied Energy, Elsevier, vol. 178(C), pages 647-659.
    4. Wolf, André & Wenzel, Lars, 2015. "Welfare implications of power rationing: An application to Germany," Energy, Elsevier, vol. 84(C), pages 53-62.
    5. Golan, Amos & Judge, George G. & Miller, Douglas, 1996. "Maximum Entropy Econometrics," Staff General Research Papers Archive 1488, Iowa State University, Department of Economics.
    6. Al-Wakeel, Ali & Wu, Jianzhong & Jenkins, Nick, 2017. "k-means based load estimation of domestic smart meter measurements," Applied Energy, Elsevier, vol. 194(C), pages 333-342.
    7. Kankal, Murat & AkpInar, Adem & Kömürcü, Murat Ihsan & Özsahin, Talat Sükrü, 2011. "Modeling and forecasting of Turkey's energy consumption using socio-economic and demographic variables," Applied Energy, Elsevier, vol. 88(5), pages 1927-1939, May.
    8. Schleicher-Tappeser, Ruggero, 2012. "How renewables will change electricity markets in the next five years," Energy Policy, Elsevier, vol. 48(C), pages 64-75.
    9. McLoughlin, Fintan & Duffy, Aidan & Conlon, Michael, 2015. "A clustering approach to domestic electricity load profile characterisation using smart metering data," Applied Energy, Elsevier, vol. 141(C), pages 190-199.
    10. Hong, Tao & Fan, Shu, 2016. "Probabilistic electric load forecasting: A tutorial review," International Journal of Forecasting, Elsevier, vol. 32(3), pages 914-938.
    11. Amos Golan & Jeffrey M. Perloff & Edward Z. Shen, 2001. "Estimating A Demand System With Nonnegativity Constraints: Mexican Meat Demand," The Review of Economics and Statistics, MIT Press, vol. 83(3), pages 541-550, August.
    12. Payne, James E., 2010. "A survey of the electricity consumption-growth literature," Applied Energy, Elsevier, vol. 87(3), pages 723-731, March.
    13. Christian Growitsch & Raimund Malischek & Sebastian Nick & Heike Wetzel, 2015. "The Costs of Power Interruptions in Germany: A Regional and Sectoral Analysis," German Economic Review, Verein für Socialpolitik, vol. 16(3), pages 307-323, August.
    14. Johannes Többen & Tobias Heinrich Kronenberg, 2015. "Construction Of Multi-Regional Input--Output Tables Using The Charm Method," Economic Systems Research, Taylor & Francis Journals, vol. 27(4), pages 487-507, December.
    15. Killinger, Sven & Mainzer, Kai & McKenna, Russell & Kreifels, Niklas & Fichtner, Wolf, 2015. "A regional optimisation of renewable energy supply from wind and photovoltaics with respect to three key energy-political objectives," Energy, Elsevier, vol. 84(C), pages 563-574.
    16. Train, Kenneth & Herriges, Joseph & Windle, Robert, 1985. "Statistically adjusted engineering (SAE) models of end-use load curves," Energy, Elsevier, vol. 10(10), pages 1103-1111.
    17. Sherman Robinson & Andrea Cattaneo & Moataz El-Said, 2001. "Updating and Estimating a Social Accounting Matrix Using Cross Entropy Methods," Economic Systems Research, Taylor & Francis Journals, vol. 13(1), pages 47-64.
    18. Amos Golan & Stephen Vogel, 2000. "Estimation of Non-Stationary Social Accounting Matrix Coefficients with Supply-Side Information," Economic Systems Research, Taylor & Francis Journals, vol. 12(4), pages 447-471.
    19. Rasmus Heltberg & Thomas Channing Arndt & Nagothu Udaya Sekhar, 2000. "Fuelwood Consumption and Forest Degradation: A Household Model for Domestic Energy Substitution in Rural India," Land Economics, University of Wisconsin Press, vol. 76(2), pages 213-232.
    20. Grandjean, A. & Adnot, J. & Binet, G., 2012. "A review and an analysis of the residential electric load curve models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(9), pages 6539-6565.
    21. Jeffrey C. Peters & Thomas W. Hertel, 2016. "Matrix balancing with unknown total costs: preserving economic relationships in the electric power sector," Economic Systems Research, Taylor & Francis Journals, vol. 28(1), pages 1-20, March.
    22. Christian Growitsch & Raimund Malischek & Sebastian Nick & Heike Wetzel, 2015. "The Costs of Power Interruptions in Germany: A Regional and Sectoral Analysis," German Economic Review, Verein für Socialpolitik, vol. 16(3), pages 307-323, August.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Huang, Yunyou & Zhan, Jianfeng & Luo, Chunjie & Wang, Lei & Wang, Nana & Zheng, Daoyi & Fan, Fanda & Ren, Rui, 2019. "An electricity consumption model for synthesizing scalable electricity load curves," Energy, Elsevier, vol. 169(C), pages 674-683.
    2. Jakub Boratyński, 2016. "A Bayesian Approach to Matrix Balancing: Transformation of Industry-Level Data under NACE Revision," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 8(4), pages 219-239, December.
    3. Persson, Maria, 2007. "Trade Facilitation and the EU-ACP Economic Partnership Agreements: Who Has the Most to Gain?," Conference papers 331619, Purdue University, Center for Global Trade Analysis, Global Trade Analysis Project.
    4. G. Ferrari & G. Garau & P. Lecca, 2009. "Constructing a Social Accounting Matrix for Sardinia," Working Paper CRENoS 200902, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    5. Malin Lachmann & Jaime Maldonado & Wiebke Bergmann & Francesca Jung & Markus Weber & Christof Büskens, 2020. "Self-Learning Data-Based Models as Basis of a Universally Applicable Energy Management System," Energies, MDPI, vol. 13(8), pages 1-42, April.
    6. Roberts, Mike B. & Haghdadi, Navid & Bruce, Anna & MacGill, Iain, 2019. "Characterisation of Australian apartment electricity demand and its implications for low-carbon cities," Energy, Elsevier, vol. 180(C), pages 242-257.
    7. Klaus Mittenzwei & Wolfgang Britz, 2018. "Analysing Farm‐specific Payments for Norway using the Agrispace Model," Journal of Agricultural Economics, Wiley Blackwell, vol. 69(3), pages 777-793, September.
    8. Ni, Yuanming & Steinshamn, Stein I. & Kvamsdal, Sturla F., 2022. "Negative shocks in an age-structured bioeconomic model and how to deal with them," Economic Analysis and Policy, Elsevier, vol. 76(C), pages 15-30.
    9. Wobst, Peter & Arndt, Channing, 2004. "HIV/AIDS and Labor Force Upgrading in Tanzania," World Development, Elsevier, vol. 32(11), pages 1831-1847, November.
    10. Y.T. Bahta & B.J. Willemse & B. Grove, 2014. "The role of agriculture in welfare, income distribution and economic development of the Free State Province of South Africa: A CGE approach," Agrekon, Taylor & Francis Journals, vol. 53(1), pages 46-74, March.
    11. Ruhang, Xu, 2020. "Efficient clustering for aggregate loads: An unsupervised pretraining based method," Energy, Elsevier, vol. 210(C).
    12. Arndt, Channing, 1999. "Demand For Herbicide In Corn: An Entropy Approach Using Micro-Level Data," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 24(1), pages 1-18, July.
    13. Rongheng Lin & Budan Wu & Yun Su, 2018. "An Adaptive Weighted Pearson Similarity Measurement Method for Load Curve Clustering," Energies, MDPI, vol. 11(9), pages 1-17, September.
    14. Gianluca Trotta & Kirsten Gram-Hanssen & Pernille Lykke Jørgensen, 2020. "Heterogeneity of Electricity Consumption Patterns in Vulnerable Households," Energies, MDPI, vol. 13(18), pages 1-17, September.
    15. Fernández, Esteban & Fernández, Paula, 2008. "An extension to Sun's decomposition methodology: The Path Based approach," Energy Economics, Elsevier, vol. 30(3), pages 1020-1036, May.
    16. Zúñiga, K.V. & Castilla, I. & Aguilar, R.M., 2014. "Using fuzzy logic to model the behavior of residential electrical utility customers," Applied Energy, Elsevier, vol. 115(C), pages 384-393.
    17. Ramos Carvajal, Carmen & Fernández Vázquez, Esteban, 2002. "Temporal projection of an input-output tables series for the region of Asturias," ERSA conference papers ersa02p211, European Regional Science Association.
    18. Guo, Dongmei & Li, Qin & Liu, Peng & Shi, Xunpeng & Yu, Jian, 2023. "Power shortage and firm performance: Evidence from a Chinese city power shortage index," Energy Economics, Elsevier, vol. 119(C).
    19. Maples, Chellie H. & Hagerman, Amy D. & Lambert, Dayton M., 2022. "Ex-ante effects of the 2018 Agricultural Improvement Act’s grassland initiative," Land Use Policy, Elsevier, vol. 116(C).
    20. Sherman Robinson & Andrea Cattaneo & Moataz El-Said, 2001. "Updating and Estimating a Social Accounting Matrix Using Cross Entropy Methods," Economic Systems Research, Taylor & Francis Journals, vol. 13(1), pages 47-64.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:appene:v:225:y:2018:i:c:p:797-813. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.